Mastercard

Mastercard

Senior Software Engineer (Backend - Java)

Toronto, Canada (Ethoca), CA · Senior

Sponsorship not specifiedDetected 18 hours ago
JavaSpringDistributed SystemsCode ReviewGitAzureCI/CDRESTAI OrchestrationIncident ResponseControlsCollaborationMentoring

About the role

  • Ethoca, a Mastercard company, is transforming the way merchants and card issuers work together to combat fraud and improve the digital commerce experience.
  • Mastercard powers an inclusive digital economy by making transactions safe, simple, smart, and accessible.
  • Through secure technology, trusted partnerships, and continuous innovation, we help individuals, businesses, and governments realize their greatest potential.

Responsibilities

  • We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible.
  • Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
  • We build highly scalable, secure, and resilient technology that powers collaboration across the global payments ecosystem.
  • This role is ideal for an engineer who can independently drive initiatives, influence technical decisions, mentor others, and contribute to a culture of engineering excellence.
  • As a Senior Software Engineer, you will design, develop, and operate secure, scalable software solutions that support critical business capabilities and customer outcomes.
  • Design, develop, test, deploy, and maintain high-quality software solutions that meet Mastercard standards for security, reliability, scalability, and operational excellence.

Requirements

  • Bachelor's degree in Computer Science, Information Technology, a related field, or equivalent practical experience.
  • Expert-level proficiency with Java (17+) and Spring-based application development.
  • Demonstrated ability to investigate and resolve complex production issues through structured troubleshooting, evidence-based decision-making, and root cause analysis.
  • Strong understanding of observability practices including logging, monitoring, metrics, dashboards, distributed tracing, and reliability-oriented alerting.
  • Experience with modern data platforms and databases, including data modeling, scalability, performance, and operational trade-offs.
  • Working knowledge of authentication, authorization, secrets management, vulnerability management, and secure handling of sensitive data in regulated environments.

Nice to have

  • Experience in payments, fintech, commerce, banking, fraud prevention, or other regulated industries.
  • Experience with batch processing, workflow orchestration, or large-scale data pipelines.
  • Experience incorporating AI-enabled capabilities into products or engineering workflows.
  • We hire the most qualified candidate for the role.
  • The Reasonable Accommodations team will respond to your email promptly.
  • Corporate Security Responsibility
  • Abide by Mastercard's security policies and practices
  • Ensure the confidentiality and integrity of the information being accessed

Skills

  • Foster engineering excellence through code reviews, technical mentoring, knowledge sharing, and promotion of development best practices.
  • Continuously improve automation, testing, observability, developer experience, and software delivery processes.

Compensation

  • In line with Mastercard's total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role an

Company info

  • We are looking for a Senior Software Engineer who thrives on solving complex technical problems, takes ownership of outcomes, and enjoys building production-grade software that operates at scale.
  • Together with our customers, we're helping build a sustainable economy where everyone can prosper.

This listing is sourced directly from Mastercard's careers page and normalized into a canonical job model.